Epidural electrical spinal cord stimulation (EES) at the lumbosacral segments has been shown to be a very promising intervention capable of facilitating locomotion in rats, cats, and humans with SCI (Ichiyama, R. M., Gerasimenko, Y. P., Zhong, H., Roy, R. R. & Edgerton, V. R. Hindlimb stepping movements in complete spinal rats induced by epidural spinal cord stimulation. Neuroscience letters 383, 339-344, doi:10.1016/j.neulet.2005.04.049 (2005); Minassian, K. et al. Human lumbar cord circuitries can be activated by extrinsic tonic input to generate locomotor-like activity. Human movement science 26, 275-295, doi:10.1016/j.humov.2007.01.005 (2007); Harkema, S. et al. Effect of epidural stimulation of the lumbosacral spinal cord on voluntary movement, standing, and assisted stepping after motor complete paraplegia: a case study. The Lancet 377, 1938-1947 (2011); Gerasimenko, Y. P. et al. Epidural spinal cord stimulation plus quipazine administration enable stepping in complete spinal adult rats. J Neurophysiol 98, 2525-2536, doi:10.1152/jn.00836.2007 (2007)).
When combined with pharmacological interventions and locomotor training, EES was demonstrated to affect functional recovery, i.e., spinal rats were able to recover full weight-bearing stepping capacities on a treadmill (Edgerton, V. R. et al. Training locomotor networks. Brain research reviews 57, 241-254, doi:10.1016/j.brainresrev.2007.09.002 (2008); Ichiyama, R. M. et al. Step training reinforces specific spinal locomotor circuitry in adult spinal rats. The Journal of neuroscience: the official journal of the Society for Neuroscience 28, 7370-7375, doi:10.1523/JNEUROSCI.1881-08.2008 (2008); Courtine, G. et al. Transformation of nonfunctional spinal circuits into functional states after the loss of brain input. Nature neuroscience 12, 1333-1342, doi:10.1038/nn.2401 (2009); Musienko, P., Heutschi, J., Friedli, L., den Brand, R. V. & Courtine, G. Multi-system neurorehabilitative strategies to restore motor functions following severe spinal cord injury. Experimental neurology, doi:10.1016/j.expneurol.2011.08.025 (2011)).
In the prior art several patents regarding neuroprosthetic apparatus or systems can be found.
US2005/090756 discloses a neural spike detection system for neuroprosthetic control, wherein neural signals are received and an information signal is transmitted when a neural spike is detected.
US2004/0267320 discloses algorithm for programming a device according to the firing rate of motor neurons. In particular, electrical impulses are detected and movements are calculated from said impulses. Said impulses may be detected in a subject cerebral cortex and brain-to-arm control may be provided.
US2003/114894 discloses a surface neuroprosthetic that enables facile adjustment and fine-tuning of the local current density over the surface of a transcutaneous scanning electrode, so as to achieve optimal muscle response. In particular, a scanning electrode for neuroprosthesis applied on muscle of a limb is disclosed.
With regard to a brain spinal interface, US2011/0208265, for example, discloses a multi-programmable trial stimulator for spinal cord, among others. The stimulator can provide a wide range of frequencies, however, a specific selection of frequencies for achieving control of locomotion functions is not disclosed in said document.
US2012/0330391 discloses a method for using spinal cord stimulation to treat symptoms of motor disorders including implanting a stimulation lead within a ventral portion of the epidural space. Frequencies higher than 100 Hz with a pulse width of less than 20 μs are disclosed.
WO2012/094346 discloses a method wherein electrical stimulation is applied to a portion of a spinal cord of a patient with a neurologically derived paralysis. Optionally, the disclosed method can be repeated using electrical stimulation having different sets of parameter values to obtain quantifiable results generated by each repetition of the method. Then, a machine learning method may be executed by at least one computing device. The machine learning method builds a model of a relationship between the electrical stimulation applied to the spinal cord and the quantifiable results generated by activation of the at least one spinal circuit. A new set of parameters may be selected based on the model.
In US2002/0115945 a method for restoring gait in individuals with SCI is disclosed, wherein epidural spinal cord stimulation is combined with partial weight bearing therapy.
In EP2486897, a closed loop brain-machine interface is disclosed, wherein neural signals are acquired and translated into movements performed by a machine. Sensory feedback is also provided. Said interface can be used for restoring voluntary control of locomotion. In the disclosed interface, however, signals are acquired directly from the brain of the subject, motor commands are extracted and movements are effected by an actuator.
In WO2013/071309, transcutaneous electrical spinal cord stimulation (tESCS) is used as a noninvasive method in rehabilitation of spinal pathology. The electrical stimulation may be delivered at 5-40 Hz at 20-100 mA. As in WO2012/094346, the possibility of a method and a model of relationship between electrical stimulation and results is disclosed.
WO2007/047852 discloses a method of treating a patient by providing an electromagnetic signal. Closed-loop neuroprosthetic devices are known in the prior art for use, for example, for predicting and preventing epileptic seizures (see for example U.S. Pat. No. 8,374,696 and US2007/0067003).
There is still the need of a method for improving and restoring locomotor functions in subjects with neuromotor impairments, in particular after spinal cord injury.
It is known that EES can be useful for facilitating locomotion in subjects with spinal cord injury and Parkinson's disease.
It is also known that each EES pulse generates a reflex response in the muscle. During stepping, EMG bursts are built from a succession of these reflex responses, which are modulated naturally during the different phases of the gait-cycle, but which may also be directly affected by the parameters of stimulation (namely frequency, amplitude and pulse-width).
There is the need of a real-time control system wherein EES can be modulated, and thus optimized, during the gait-cycle during locomotion, so that a precise control of gait patterns, muscle activity, and foot trajectory can be achieved, and also for accurate upper-limb control (for precise reaching and grasping).
The control and modulation of the electrical stimulation is particularly advantageous for facilitating and improving locomotion functions.
For example, a controlled electrical stimulation helps compensating for the fatigue deriving from an external source of muscle activity. When non-controlled EES-induced locomotion is performed, fatigue yields a decreased flexion and extension pattern during stepping over time thus inducing lower stepping and eventually collapse.
It has now been found that there is a linear relationship between the frequency of electrical stimulation applied in the epidural and subdural space and relevant parameters of gait.
In particular, it has now been found that there is a linear relationship between the frequency of EES and relevant parameters of gait, in particular step height. This relationship has been used for the development of models and control algorithms which allow for a controlled modulation of locomotor patterns through the adaptation of EES frequency, thus achieving real-time control of locomotion.
It has been found that EES frequency clearly and consistently modulates locomotor patterns in subjects with SCI or with lesions of the upper limbs or head in unique and predictive ways.
Gait features that were most correlated with changes in EES frequency can be grouped into functional clusters of flexion, extension, speed and variability along Principal Component Analysis (PC).
In particular, it has been found that the relationship between EES frequency and step height (i.e., the maximum height reached by the foot during each gait cycle) is close to linear and step height is modulated with the frequency, which allowed us to build a linear input-output model, particularly useful for EES control.
It has also been found by the inventors of the present disclosure that EES applied at lumbar and sacral locations promotes whole-limb flexion and extension, respectively. Also, when EES is applied on the lateral side of the spinal cord the effects of the stimulation are restricted to the limbs on the stimulated side. Real-time algorithms have thus been developed to apply EES to different sites of stimulation, in some examples to 4 or more sites based on the actual phase of the gait cycle.
It has further been found that the timing at which stimulation at each site is turned on and off is critical. Each site of EES stimulation modulates a specific functional effect, including facilitation of extension and flexion of the left versus right limbs, based on the actual phase of the locomotor movement.
This rolling burst EES pattern markedly increases the EMG activity of limb muscles, and promotes locomotion with improved interlimb and intralimb coordination, and superior weight-bearing levels compared to continuous EES.
In particular, it has also been found that subdural stimulation promotes coordinated, weight bearing stepping of a paralyzed limb with improved gait characteristics. More in particular, subdural stimulation requires reduced electrical current threshold to be effective and achieves more specific unilateral recruitment of motor neurons.